Sep 2026· Journal of the American Chemical Society· 0 citations· 86 references
Receptor Mechanisms and Signaling
Abstract
Membrane proteins and their complexes play essential roles in various biological processes and are, therefore, major targets in drug development. Although atomic-resolution structures of many membrane proteins are available, probing their function-associated dynamics remains essential to understand their molecular mechanisms. In this study, we developed an isotope-labeling method using mammalian cells for high-sensitivity NMR studies of membrane proteins and their complexes. Using Expi293F cells, we established a strategy to achieve high-level (>70%) deuteration and 13C-methyl selective labeling. An application to a human GPCR, β2-adrenergic receptor (β2AR), resulted in marked line narrowing and a three- to four-fold increase in the S/N ratio. We also found that the inverse agonist-bound β2AR adopted three distinct conformations, one of which has not been clearly identified without the extensive deuteration. Furthermore, the strategy enables the NMR detection of the human membrane protein complex CD19-CD81, an essential co-receptor in B-cell activation, validating their stable interaction. The strategy developed here substantially expands the utility of NMR for various biological and pharmacological studies that require mammalian cell systems.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
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Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.